/*Run Online (Liu method)*/
private void btnRunOnl_Click(List <double> training_data, List <double> streaming_data, int period, int NLength, int maxEntry, int minEntry, int R, int D)
{
//create a new buffer. In this demo, the buffer is training_data (edit later):
List <double> this_buffer = new List <double>();
this_buffer.AddRange(training_data);
// Store furnitures in RTree
int this_id_item = int.MinValue;
List <int> this_id_itemList = new List <int>();
RTree <int> this_RTree = new RTree <int>(maxEntry, minEntry);
List <Rectangle> this_recList = new List <Rectangle>();
// Call 'Run Offline' for the first time, store results into variables ("this" object):
List <double> discord_firsttime = RunOfflineMinDist(training_data, NLength, maxEntry, minEntry, R, D, ref this_id_item, ref this_id_itemList, ref this_recList, ref this_RTree, true);
// Store current discord in buffer
double this_best_so_far_dist = discord_firsttime[0];
double this_best_so_far_loc = discord_firsttime[1];
//store the last subsequence of the buffer:
List <double> last_sub = this_buffer.GetRange(this_buffer.Count - NLength, NLength);
// STREAMING: keep streaming until we have no more data points
for (int index_stream = 0; index_stream < streaming_data.Count; index_stream++)
{
var watch = System.Diagnostics.Stopwatch.StartNew();///calc execution time
double new_data_point = streaming_data[index_stream];
//update last_sub at time t to get new_sub at time (t+1):
last_sub.Add(new_data_point);
last_sub.RemoveAt(0);
List <double> new_sub = last_sub; // the same object
// Insert the new entry into the tree:
this_id_item++;
// Add the new rec to the tree:
Rectangle new_rec = new Rectangle(Utils.MathFuncs.PAA_Lower(new_sub, D, R).ToArray(), Utils.MathFuncs.PAA_Upper(new_sub, D, R).ToArray(), this_buffer.Count - NLength + 1 + index_stream);
this_RTree.Add(new_rec, this_id_item);
this_recList.Add(new_rec);
this_id_itemList.Add(this_id_item);
//remove the oldest entry:
this_RTree.Delete(this_recList[index_stream], this_id_itemList[index_stream]);
//get the first sub before update the buffer (help to find the small match in Liu's method)
List <double> first_sub = this_buffer.GetRange(0, NLength);
// update buffer:
this_buffer.Add(new_data_point);
this_buffer.RemoveAt(0);
/* 'til now, we have already updated the tree.
* from now on, almost just copy the offline code:
*/
//Method 1: just re-order the 2 loops:
//RunOnline_Method1(this_buffer, index_stream);
//Method 2: Liu's algorithm:
//Note: Method_2 includes method_1 (case a)
//RunOnline_LiuMethod_origin(this_buffer, index_stream, first_sub);
//Method 3: motified_Liu's
List <double> discord_Liu = RunOnline_LiuMethod_edited(this_buffer, index_stream, first_sub, this_RTree, this_best_so_far_dist, (int)this_best_so_far_loc, NLength, D);
this_best_so_far_dist = discord_Liu[0];
this_best_so_far_loc = discord_Liu[1];
watch.Stop(); //stop timer
long elapsedMs = watch.ElapsedMilliseconds;
//this.txtExeTime.Text = elapsedMs.ToString();
Console.WriteLine("ExeTime_Online=" + elapsedMs.ToString());
// Useless variable to pass parameter
int dumb = 0;
List <int> dumb_list = new List <int>();
List <Rectangle> dumb_rectlist = new List <Rectangle>();
RTree <int> dumb_rtree = new RTree <int>(maxEntry, minEntry);
//call offline version to assure the results and compare the time executions:
var watch2 = System.Diagnostics.Stopwatch.StartNew();///calc execution time offline
List <double> discord_offline = RunOfflineMinDist(training_data, NLength, maxEntry, minEntry, R, D, ref dumb, ref dumb_list, ref dumb_rectlist, ref dumb_rtree, false);
double this_best_so_far_dist_offline = discord_offline[0];
watch2.Stop(); //stop timer
long this_exeTimeOffline = watch2.ElapsedMilliseconds;
//check:
if (Math.Abs(this_best_so_far_dist - this_best_so_far_dist_offline) < 10e-7)
{
Console.WriteLine("checked, ok.");
if (elapsedMs > this_exeTimeOffline)
{
Console.WriteLine("Online takes more time than Offline !!!");
}
}
else
{
Console.WriteLine("this.best_so_far_dist = " + this_best_so_far_dist);
Console.WriteLine("this.best_so_far_dist_Offline = " + this_best_so_far_dist_offline);
Console.WriteLine("The results are different. Stop Streaming !!!");
return;
}
Console.WriteLine("------------------------");
} // end For loop (streaming)
Console.WriteLine("--- Streaming's done (run out of data) ---");
} //end btnRunOnl_Click function
} //end btnRunOnl_Click function
/*Run Online - new method (inner loop only)*/
private void Btn_NewOnline_Click(List <double> training_data, List <double> streaming_data, int period, int NLength, int maxEntry, int minEntry, int R, int D)
{
//create a new buffer. In this demo, the buffer is training_data (edit later):
List <double> this_buffer = new List <double>();
this_buffer.AddRange(training_data);
// Store furnitures in RTree
int this_id_item = int.MinValue;
List <int> this_id_itemList = new List <int>();
RTree <int> this_RTree = new RTree <int>(maxEntry, minEntry);
List <Rectangle> this_recList = new List <Rectangle>();
// Call 'Run Offline' for the first time, store results into variables ("this" object):
List <double> discord_firsttime = RunOfflineMinDist(training_data, NLength, maxEntry, minEntry, R, D, ref this_id_item, ref this_id_itemList, ref this_recList, ref this_RTree, true);
double this_best_so_far_dist_TheMostDiscord = discord_firsttime[0];
//store the last subsequence of the buffer:
List <double> last_sub = this_buffer.GetRange(this_buffer.Count - NLength, NLength);
// STREAMING: keep streaming until we have no more data points
for (int index_stream = 0; index_stream < streaming_data.Count; index_stream++)
{
var watch = System.Diagnostics.Stopwatch.StartNew();///calc execution time
double new_data_point = streaming_data[index_stream];
//update last_sub at time t to get new_sub at time (t+1):
last_sub.Add(new_data_point);
last_sub.RemoveAt(0);
List <double> new_sub = last_sub; // the same object
// Insert the new entry into the tree:
this_id_item++;
// Add the new rec to the tree:
Rectangle new_rec = new Rectangle(Utils.MathFuncs.PAA_Lower(new_sub, D, R).ToArray(), Utils.MathFuncs.PAA_Upper(new_sub, D, R).ToArray(), this_buffer.Count - NLength + 1 + index_stream);
this_RTree.Add(new_rec, this_id_item);
this_recList.Add(new_rec);
this_id_itemList.Add(this_id_item);
//remove the oldest entry:
this_RTree.Delete(this_recList[index_stream], this_id_itemList[index_stream]);
// update buffer:
this_buffer.Add(new_data_point);
this_buffer.RemoveAt(0);
/* 'til now, we have already updated the tree.
* from now on, almost just copy the offline code:
*/
//Run new_online_algorithm:
NewOnlineAlgorithm(this_buffer, 2 * period, index_stream, period, new_sub, this_RTree, NLength, D, R, maxEntry, minEntry, ref this_best_so_far_dist_TheMostDiscord);
watch.Stop(); //stop timer
long elapsedMs = watch.ElapsedMilliseconds;
//this.txtExeTime.Text = elapsedMs.ToString();
Console.WriteLine("ExeTime_Online=" + elapsedMs.ToString());
Console.WriteLine("------------------------");
} // end For loop (streaming)
Console.WriteLine("--- Streaming's done (run out of data) ---");
}
////////////// Main Functions //////////////
/*Run new offline (minDist) */
public static List <double> RunOfflineMinDist(List <double> inputData, int NLength, int maxEntry, int minEntry, int R, int D, ref int this_id_item, ref List <int> this_id_itemList, ref List <Rectangle> this_rectList, ref RTree <int> this_RTree, bool is_first_time)
{
int id_item = int.MinValue;
RTree <int> rtree = new RTree <int>(maxEntry, minEntry);
List <int> candidateList = new List <int>();
List <int> beginIndexInner = new List <int>();
List <int> indexOfLeafMBRS = new List <int>();
double best_so_far_dist = 0;
int best_so_far_loc = -1;
double nearest_neighbor_dist = 0;
double dist = 0;
bool break_to_outer_loop = false;
bool[] is_skipped_at_p = new bool[inputData.Count];
for (int i = 0; i < inputData.Count; i++)
{
is_skipped_at_p[i] = false;
}
if (minEntry > maxEntry / 2)
{
MessageBox.Show("Requirement: MinNodePerEntry <= MaxNodePerEntry/2");
return(new List <double> {
best_so_far_dist, best_so_far_loc
});
}
List <Rectangle> recList = new List <Rectangle>();
List <int> id_itemList = new List <int>();
for (int i = 0; i <= inputData.Count - NLength; i++)
{
List <double> subseq = inputData.GetRange(i, NLength);
id_item++;
Rectangle new_rec = new Rectangle(MathFuncs.PAA_Lower(subseq, D, R).ToArray(), MathFuncs.PAA_Upper(subseq, D, R).ToArray(), i);
rtree.Add(new_rec, id_item);
recList.Add(new_rec);
id_itemList.Add(id_item);
}
Dictionary <int, Node <int> > nodeMap = rtree.getNodeMap();
List <Node <int> > leafNodes = nodeMap.Values.Where(node => node.level == 1).OrderBy(node => node.entryCount).ToList();
List <Rectangle> leafMBRs = leafNodes.Select(node => node.mbr).ToList(); // List rectangle of leaf nodes in order of list leafNodes
for (int i = 0; i < leafNodes.Count; i++)
{
List <Rectangle> leafEntries = leafNodes[i].entries.Where(mbr => mbr != null).Select(mbr => mbr).ToList();
if (leafEntries.Count > 0)
{
int beginIndex = candidateList.Count;
candidateList.AddRange(leafEntries.Select(mbr => mbr.getIndexSubSeq()));
beginIndexInner.AddRange(Enumerable.Repeat(beginIndex, leafEntries.Count));
indexOfLeafMBRS.AddRange(Enumerable.Repeat(i, leafEntries.Count));
}
}
for (int i = 0; i < candidateList.Count; i++)//outer loop
{
int p = candidateList[i];
// rectangle of subseq in p postion
if (is_skipped_at_p[p])
{
//p was visited at inner loop before
continue;
}
else
{
List <double> subseq_p = inputData.GetRange(p, NLength);
//Rectangle p_rectangle = recList[p];
List <double> P_PAA = MathFuncs.PAA(subseq_p, D);
nearest_neighbor_dist = Constants.INFINITE;
List <bool> eliminatedMBR = new List <bool>();
for (int k = 0; k < leafMBRs.Count; k++)
{
eliminatedMBR.Add(false);
}
int indexMBRLeaf = -1;
int num_leaf_skips = 0;
for (int j = 0; j < candidateList.Count; j++)// inner loop
{
// int q = innerList[j];
int index_inner = (beginIndexInner[i] + j) % candidateList.Count;
int q = candidateList[index_inner];
int index_MBRInnner = (beginIndexInner[i] + j) % candidateList.Count;
int MBRInnner = indexOfLeafMBRS[index_MBRInnner];
if (indexMBRLeaf < MBRInnner)//the first entry of the next node ?
{
indexMBRLeaf++;
/* Test:
* if (indexMBRInnner[j] == MBRInnner)
* Console.WriteLine("OK");*/
//calc minDist:
//double minDist = MathFuncss.MINDIST(p_rectangle, leafMBRs[MBRInnner], (NLength / (double)(D)));
double minDist = MathFuncs.MINDIST(P_PAA, leafMBRs[MBRInnner], (NLength / (double)(D)));
//if (minDist_keo > minDist)
//{
// Console.WriteLine("STOPPP");
// return;
//}
if (minDist >= nearest_neighbor_dist)
{
num_leaf_skips++;
eliminatedMBR[MBRInnner] = true;
continue;// pruned => skip to the next one
}
else
{
if (Math.Abs(p - q) < NLength)
{
continue;// self-match => skip to the next one
}
//calculate the Distance between p and q
dist = MathFuncs.EuDistance(subseq_p, inputData.GetRange(q, NLength));
if (dist < best_so_far_dist)
{
//skip the element q at oute_loop, 'cuz if (p,q) is not a solution, neither is (q,p).
is_skipped_at_p[q] = true;
break_to_outer_loop = true; //break, to the next loop at outer_loop
break; // break at inner_loop first
}
if (dist < nearest_neighbor_dist)
{
nearest_neighbor_dist = dist;
}
}
}
else // still the same node
{
if (eliminatedMBR[MBRInnner]) // can prune ?
{
continue;
}
else //do it normally
{
if (Math.Abs(p - q) < NLength)
{
continue;// self-match => skip to the next one
}
else
{
//calculate the Distance between p and q
dist = MathFuncs.EuDistance(subseq_p, inputData.GetRange(q, NLength));
if (dist < best_so_far_dist)
{
//skip the element q at oute_loop, 'cuz if (p,q) is not a solution, neither is (q,p).
is_skipped_at_p[q] = true;
break_to_outer_loop = true; //break, to the next loop at outer_loop
break; // break at inner_loop first
}
if (dist < nearest_neighbor_dist)
{
nearest_neighbor_dist = dist;
}
}
}
} //end ELSE
} //end for inner loop
//Console.WriteLine("num_leaf_skips="+ num_leaf_skips);
if (break_to_outer_loop)
{
break_to_outer_loop = false; //reset
continue; //go to the next p in outer loop
}
if (nearest_neighbor_dist > best_so_far_dist)
{
best_so_far_dist = nearest_neighbor_dist;
best_so_far_loc = p;
}
}
}//end outer loop
if (is_first_time)
{
this_id_item = id_item;
this_id_itemList = id_itemList;
this_RTree = rtree;
this_rectList = recList;
}
return(new List <double> {
best_so_far_dist, best_so_far_loc
});
}